Answers to SAS Certification Assignments

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[edit]

Section 1

Exercise 1:input

Exercise 2:infile, input

Exercise 3:

data students; infile 'C:\Documents and Settings\Yuan-Ting Wang\UserData\cat.txt' (obs=10); run;

data students; set cats (obs=10); run;

Exercise 4: once

Exercise 5: missover and truncover

Exercise 6: a.Change (firstobs=2) to (obs=3) b.Change (firstobs=2) to (firstobs=2 obs=3)

[edit]

Section 2

[edit]

example 1

data sealife;
input name $ family $ length ;
datalines;
beluga   whale   15
whale    shark   40
basking  shark   30
gray     whale   50
mako     shark   12
sperm    whale   60
dwarf    shark   .5
whale    shark   40
humpback   .     50
blue     whale   100
killer   whale   30
;
run; 

data newsealife;
set sealife;
newlength=length;
format newlength 10.2;
run;

proc print data=newsealife;
var newlength;
run;

[edit]

example 2

data candy;
input Name $ ClassRm Month Day Year Candy $ Quantity   ;
cards;
Adriana    21    3   2  2000  MP    7
Nathan     14    2   28 2000  CD   19
Matthew    14    3   1  2000  CD   14
Claire     14    3   3  2000  CD   11
Caitlin    21    2   24 2000  CD    9
Ian        21    3   3  2000  MP   18
Chris      14    2   18 2000  CD    6
Anthony    21    6   1  2000  MP   13
Stephen    14    3   25 2000  CD   10
Erika      21    3   25 2000  MP  17
;
run;

proc means data=candy min max;
var quantity;
run;

[edit]

example 3

data candy;
input Name $ ClassRm Month Day Year Candy $ Quantity   ;
cards;
Adriana    21    3   2  2000  MP    7
Nathan     14    2   28 2000  CD   19
Matthew    14    3   1  2000  CD   14
Claire     14    3   3  2000  CD   11
Caitlin    21    2   24 2000  CD    9
Ian        21    3   3  2000  MP   18
Chris      14    2   18 2000  CD    6
Anthony    21    6   1  2000  MP   13
Stephen    14    3   25 2000  CD   10
Erika      21    3   25 2000  MP   17
;
run; 

data candy1;
set candy;
/*if (quantity<12) then quantity=1;
else quantity=2;*/
/* Here's another way to group*/
group=1; 
if (quantity>=12) then group=2;
run; 
 

proc print data=candy1;
var group;
run;

[edit]

example 4

data candy;
input Name $ ClassRm Month Day Year Candy $ Quantity   ;
cards;
Adriana    21    3   2  2000  MP    7
Nathan     14    2   28 2000  CD   19
Matthew    14    3   1  2000  CD   14
Claire     14    3   3  2000  CD   11
Caitlin    21    2   24 2000  CD    9
Ian        21    3   3  2000  MP   18
Chris      14    2   18 2000  CD    6
Anthony    21    6   1  2000  MP   13
Stephen    14    3   25 2000  CD   10
Erika      21    3   25 2000  MP   17
;
run; 

data candy1;
set candy;
/*if (quantity<12) then quantity=1;
else quantity=2;*/
/* Here's another way to group*/
group=1; 
if (quantity>=12) then group=2;
run;
 

proc print data=candy1;
var group;
run;

proc sort data=candy1 out=candy2;
by group;
run;

proc print data=candy2;
run; 

proc means data=candy2 mean;
var quantity;
by group; 

run;

[edit]

example 5

data candy;
input Name $ ClassRm Month Day Year Candy $ Quantity   ;
cards;
Adriana    21    3   2  2000  MP    7
Nathan     14    2   28 2000  CD   19
Matthew    14    3   1  2000  CD   14
Claire     14    3   3  2000  CD   11
Caitlin    21    2   24 2000  CD    9
Ian        21    3   3  2000  MP   18
Chris      14    2   18 2000  CD    6
Anthony    21    6   1  2000  MP   13
Stephen    14    3   25 2000  CD   10
Erika      21    3   25 2000  MP   17
;
run;

data candy1;
set candy;
/*if (quantity<12) then quantity=1;
else quantity=2;*/
/* Here's another way to group*/
group=1; 
if (quantity>=12) then group=2;
run; 


proc print data=candy1;
var group;
run;  

proc sort data=candy1 out=candy2;
by group;
run;

proc print data=candy2;
run;

/*proc means data=candy2 mean;
var quantity;
by group;

run;*/

proc means data=candy2 mean;
var quantity;
class group;
run;

[edit]

Session 3

[edit]

Exercise 3.1

data candy;
input Name $ ClassRm Month Day Year Candy $ Quantity   ;
cards;
Adriana    21    3   2  2000  MP    7
Nathan     14    2   28 2000  CD   19
Matthew    14    3   1  2000  CD   14
Claire     14    3   3  2000  CD   11
Caitlin    21    2   24 2000  CD    9
Ian        21    3   3  2000  MP   18
Chris      14    2   18 2000  CD    6
Anthony    21    6   1  2000  MP   13
Stephen    14    3   25 2000  CD   10
Erika      21    3   25 2000  MP   17
;
run;

ods html file='c:\temp\corr.html';
title 'Candy data'; 

proc corr data=candy;
var classrm quantity;
run;
ods html close;

[edit]

Exercise 3.2

data funds;
input name $ return 44-47 SDAR ;
cards;
Group Securities. Common Stock Fund        15.1     19.1
Incorporated Investors                     14.0     25.5
Investment Company of America              17.4     21.8
Investors Mutual                           11.3     12.5
Loomis-Sales Mutual Fund                   10.0     10.4
Massachusetts Investors Trust              16.2     20.8
National Investors Corporation             18.3     19.9
National Securities-Income Series          12.4     17.8
New England Fund                           10.4     10.2
Massachusetts Investors-Growth Stock       18.6     22.7
Group Securities. Fully Administered Fund  11.4     14.1
;
run;
proc print data=funds;
run;
data funds1;
set funds;
first5=substr(name,);
run;

proc print data=funds1;
run;

proc sort data=funds1;
by name;
run;

proc print data=funds1;
run;

[edit]

Exercise 3.3

data hw;
input time days;
cards;
100 3
150 4
 99 5
  . 6
160 3
 80 .
200 3
;
run; 

data hw1;
set hw;
avehw=mean(time/days);
run;
proc print data=hw1;
run;

[edit]

Exercise 3.4

data salary;
input FIELD$1-35  WOMEN    MEN;
cards;
Business, Finance, Etc.               9.3    13.0
Labor Economics                      10.3    12.0
Monetary-Fiscal                       8.0    11.6
General Economic Theory               8.7    10.8
Population, Welfare Programs, Etc.   12.0    11.5
Economic Systems and Development      9.0    12.2
;
run; 

proc print data=salary;
run; 

data salary1;
set salary;
array T {2} women men;
do i=1 to 2;
T[i]=T[i]*1000;
end;
run;
proc print data=salary1;
run;

[edit]

Section 4

[edit]

4.1 and 4.2

data fitness; 
    input Age Weight Oxygen RunTime RestPulse RunPulse MaxPulse @@; 
    datalines; 
 44 89.47 44.609 11.37 62 178 182   40 75.07 45.313 10.07 62 185 185 
 44 85.84 54.297  8.65 45 156 168   42 68.15 59.571  8.17 40 166 172 
 38 89.02 49.874  9.22 55 178 180   47 77.45 44.811 11.63 58 176 176 
 40 75.98 45.681 11.95 70 176 180   43 81.19 49.091 10.85 64 162 170 
 44 81.42 39.442 13.08 63 174 176   38 81.87 60.055  8.63 48 170 186 
 44 73.03 50.541 10.13 45 168 168   45 87.66 37.388 14.03 56 186 192 
 45 66.45 44.754 11.12 51 176 176   47 79.15 47.273 10.60 47 162 164 
 54 83.12 51.855 10.33 50 166 170   49 81.42 49.156  8.95 44 180 185 
 51 69.63 40.836 10.95 57 168 172   51 77.91 46.672 10.00 48 162 168 
 48 91.63 46.774 10.25 48 162 164   49 73.37 50.388 10.08 67 168 168 
 57 73.37 39.407 12.63 58 174 176   54 79.38 46.080 11.17 62 156 165 
 52 76.32 45.441  9.63 48 164 166   50 70.87 54.625  8.92 48 146 155 
 51 67.25 45.118 11.08 48 172 172   54 91.63 39.203 12.88 44 168 172 
 51 73.71 45.790 10.47 59 186 188   57 59.08 50.545  9.93 49 148 155 
 49 76.32 48.673  9.40 56 186 188   48 61.24 47.920 11.50 52 170 176 
 52 82.78 47.467 10.50 53 170 172 
 ; 
 run;
proc reg data=fitness outest=result1 noprint;
 model age=Restpulse weight;
 output out=fitness1 r=resid;
 run;
proc print data=fitness1;
run;
data fitness2;
set fitness1;
newvar=abs(resid) ;
run;
proc sort data=fitness2;
by descending newvar;
run;
proc print data=fitness2;
run;
data fitness3;
set fitness2;
if newvar>8 then delete;
run;
proc print data=fitness3;
run; 
proc reg data=fitness3 outest=result2 noprint;
 
model age=Restpulse weight;

run;

proc print data=result1;
run;
proc print data=result2;
run; 

proc plot data=fitness3;
plot age*weight;
run;

proc plot data=fitness;
plot age*weight;
run;

[edit]

4.3

data speeding;
input x;
datalines;
2  
3 
2  
1  
3  
6  
8  
9 
10 
13  
2
12 
;
run;

data month;
month=1;
output;
do i=1 to 11;
month=month+1;
output;
end;
run;

data fullinfo;
merge month speeding;
run;

proc print data=fullinfo;
run;

[edit]

Section 5

[edit]

example 1

data phone;
input City $11. @12 State $ Zip $ Phonenum $;
cards;
cary        NC  27513  6224549
cary        NC  27513  6223251
chapel-hill NC  27514  9974794
raleigh     NC  27612  6970450
raleigh     NC  27612  6791125
cary        NC  27513  6224550
;
run;
proc print data=phone;
run;

data phone1;
set phone;
areacode=substr(phonenum,1,3);
len=length(city);
run;
proc print data=phone1;
run;

[edit]

example 2

data GDP;
input year $ y x;
cards;
 1982    100.0000    100.0000
 1983    100.5000    102.0000
 1984    100.4000    104.6000
 1985    101.3000    106.1000
 1986    104.4000    108.3000
 1987    104.3000    109.4000
 1988    104.4000    110.4000
 1989    103.0000    109.5000
 1990    103.2000    109.7000
 1991    103.9000    110.1000
 ;
 run;
proc print data=gdp;
run; 

proc reg data=gdp;
model y=x;
run;

[edit]

example 3

data GDP2;
input year $ @11 y 3.2  @23 x 3.2;
cards;
 1982    100.0000    100.0000
 1983    100.5000    102.0000
 1984    100.4000    104.6000
 1985    101.3000    106.1000
 1986    104.4000    108.3000
 1987    104.3000    109.4000
 1988    104.4000    110.4000
 1989    103.0000    109.5000
 1990    103.2000    109.7000
 1991    103.9000    110.1000
 ;
 run;

proc print data=gdp2;
run;

proc reg data=gdp2;
model y=x;
run;

Another way to solve the problem:

data GDP;
input year $  y    x ;
cards;
 1982    100.0000    100.0000
 1983    100.5000    102.0000
 1984    100.4000    104.6000
 1985    101.3000    106.1000
 1986    104.4000    108.3000
 1987    104.3000    109.4000
 1988    104.4000    110.4000
 1989    103.0000    109.5000
 1990    103.2000    109.7000
 1991    103.9000    110.1000
 ;
 run;
proc print data=gdp;
run;

proc reg data=gdp;
model y=x;
run;

data gdp1;
set gdp;
newy=(y/100);
newx=(x/100);
run;
proc print data=gdp1;
run;

proc reg data=gdp1;
model newy=newx;
run;

[edit]

example 4

data regression;
input y x2 $ x3;
cards;
 10     1     1
 8     2     3
 6     3     5
 4     4     7
 2     5     9
 0     6    11
 2     7    13
;
run;
proc print data=regression;
run;

proc reg data=regression;
model y=x3;
run;


data new;
set regression;
ly=log(y);
lx3=log(x3);
run;

proc print data=new;
run; 

proc reg data=new;
model ly=lx3;
run;

[edit]

example 5

proc print data=ny(obs=20);
var COUNTY_NAME F_FUNDS T_FUNDS
;
run;

[edit]

Section 6

data test;
set sashelp.air;
format date juldate.;
run;
proc print data=test(obs=10);
run;

data _null_;
set sashelp.air (obs=50);
file 'c:\Temp\air50.txt';
put @1 date date7. @9 air 4. ;
run;

data test1;
infile 'c:\Temp\air50.txt';
input date date9. air;
run;

proc print data=test1(obs=10);
run;

[edit]

Session 7

[edit]

exercise 1

data airt;
set sashelp.air;
day=day(date); 
mo=month(date);
yr=year(date);
decade=(int(yr/10)-190)*10;
run;

proc print data=airt;
run;

data airt;
set airt;
drop day date;
run;
proc print data=airt;
run; 

proc means data=airt;
by decade;
var air;
output out=maxair max=mair;
run;
proc print data=maxair;
run;
data test;
set maxair;
drop _type_ _freq_;
run;

data 'c:\temp\airmax.sas7bdat';
set test;
run;

data airmax;
set 'c:\temp\airmax.sas7bdat';
run;

proc sort data=airmax;
by decade;
run;
proc print data=airmax;
run;

proc sort data=airt;
by decade;
run;

proc print data=airt;
run;

data final;
merge airt airmax;
by decade;
relative=((mair-air)/mair)*100;
run;

proc print data=final;
run;

[edit]

exercise 2

First you have to save the data(1992-2002) in your computer, and then try to import it into SAS. Then do the following steps:

data employment;
set employment1;
run;

data employment2;
input Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec;
cards; 
2003 74.4 74.4 74.2 74.2 74.1 74.0 74.0 73.8 73.9 73.7 73.3 73.3   
2004 72.7 73.2 72.8 72.9 73.1 73.1 73.1 73.2 73.0 72.9 72.7 72.4 
;
run; 

data combine;
set employment employment2;
run;
proc print data=combine;
run;

[edit]

exercise 3

Use 'nodupkeys' which introduced in the workshop last week.

[edit]

Session 8

[edit]

exercise 1

/*data base;
array inning (*) var2-var10;
set baseball;
runs=0;
do i = 1 to 9;
runs=runs+ inning(i);
end;
rename var1=team;
keep team runs;
run;
*/
* CLAMCHOWFF VEGMED;

data soup2;
set soup;
array flavor (*) var3-var59;
rename var1=street var2=city;
ff=0; vm=0;
do i=1 to 57;
 if (flavor(i)='CLAMCHOWFF') then FF=1;
 if (flavor(i)='VEGMED') then VM=1;
 end;
drop i;
run;

data soup3;
set soup2;
array flavor (*) var3-var59;
nchick=0;
do i=1 to 57;
if (substr(flavor(i) ,1,5)='CHICK') then nchick=nchick+1;
end;
run;


data soup4;
set soup;
array flavor (*) var3-var59;
newchick=0;
do i=1 to 57;
if (index(flavor(i),'CHICK')>0) then newchick=newchick+1;
end;

Retrieved from "http://wiki.binghamton.edu/index.php/Answers_to_SAS_Certification_Assignments"

Category: SAS Certification Workshops

Answers to SAS Certification Assignments

From BingWiki

Contents

Section 1

Section 2

example 1

example 2

example 3

example 4

example 5

Session 3

Exercise 3.1

Exercise 3.2

Exercise 3.3

Exercise 3.4

Section 4

4.1 and 4.2

4.3

Section 5

example 1

example 2

example 3

example 4

example 5

Section 6

Session 7

exercise 1

exercise 2

exercise 3

Session 8

exercise 1

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